Flux MCP Integration Guide

MCP (Model Context Protocol) is a model context protocol launched by Anthropic that allows AI models (such as Claude, GPT, etc.) to call external tools through a standardized interface. With the Flux MCP Server provided by 费思量-API, you can directly generate and edit AI images within AI clients like Claude Desktop, VS Code, Cursor, and more.

Feature Overview

Flux MCP Server offers the following core features:

  • Text-to-Image Generation — Generate high-quality images from text prompts
  • Image Editing — Edit existing images based on text instructions
  • Multi-Model Support — Supports various models including Flux Pro, Flux Dev, Flux Schnell, Flux Kontext, etc.
  • Model Query — View all available models and their capabilities
  • Task Query — Monitor generation progress and retrieve results

Prerequisites

Before use, you need to obtain an 费思量-API API Token:

  1. Register or log in to the 费思量-API Platform
  2. Go to the Flux Images API page
  3. Click "Acquire" to get the API Token (free quota granted on first application)

Installation and Configuration

Method 1: pip Installation (Recommended)

pip install mcp-flux-pro

Method 2: Source Installation

git clone https://github.com/AceDataCloud/FluxMCP.git
cd FluxMCP
pip install -e .

After installation, you can start the service using the mcp-flux-pro command.

Using in Claude Desktop

Edit the Claude Desktop configuration file:

  • macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
  • Windows: %APPDATA%\Claude\claude_desktop_config.json

Add the following configuration:

{
  "mcpServers": {
    "flux": {
      "command": "mcp-flux-pro",
      "env": {
        "ACEDATACLOUD_API_TOKEN": "your API Token"
      }
    }
  }
}

If using uvx (no need to pre-install packages):

{
  "mcpServers": {
    "flux": {
      "command": "uvx",
      "args": ["mcp-flux-pro"],
      "env": {
        "ACEDATACLOUD_API_TOKEN": "your API Token"
      }
    }
  }
}

Save the configuration and restart Claude Desktop to use Flux-related tools in conversations.

Using in VS Code / Cursor

Create .vscode/mcp.json in the project root directory:

{
  "servers": {
    "flux": {
      "command": "mcp-flux-pro",
      "env": {
        "ACEDATACLOUD_API_TOKEN": "your API Token"
      }
    }
  }
}

Or use uvx:

{
  "servers": {
    "flux": {
      "command": "uvx",
      "args": ["mcp-flux-pro"],
      "env": {
        "ACEDATACLOUD_API_TOKEN": "your API Token"
      }
    }
  }
}

Available Tools

Tool Name Description
flux_generate_image Generate images from text prompts
flux_edit_image Edit existing images based on text instructions
flux_get_task Query the status of a single task
flux_get_tasks_batch Batch query task statuses
flux_list_models List all available models and their capabilities
flux_list_actions List all available tools and workflow examples

Usage Examples

After configuration, you can directly invoke these features in AI clients using natural language, for example:

  • "Help me generate a cyberpunk-style city nightscape with Flux"
  • "Change the background of this photo to a beach"
  • "Use the Flux Kontext Pro model to edit this image and change the clothing color to red"
  • "List all available Flux models"

More Information